P.073 Factors associated with fatigue in children and adolescents with Duchenne muscular dystrophy: A Canada-wide cross-sectional survey
Bibliographic record
Abstract
Background: Fatigue is frequent and disabling in adults with neuromuscular disorders, but not well characterized in paediatric neuromuscular disorders. Recently, fatigue was reported to be associated with poor health-related quality of life in children with Duchenne muscular dystrophy (DMD). Determinants of fatigue—a modifiable symptom—have not been studied in DMD. Our objective was to explore risk factors for fatigue in children with DMD. Methods: Patients aged 4–17 years identified via the Canadian Neuromuscular Disease Registry received mailed questionnaires. Fatigue was assessed using the PedsQLTM Multidimensional Fatigue Scale (patient- and parent-report). Standardized measures for depressive symptoms, sleep disturbances, functional ability and physical activity were used. Spearman’s correlations and Wilcoxon rank-sum tests were computed. Results: Of 194 eligible patients, 64 have responded to date. DMD patients reported greater fatigue than healthy controls from published data. Depressive symptoms were associated with greater fatigue, by patient-report (ρ=-0.44, P<0.001) and parent-report (ρ=-0.40, P=0.002). Sleep disturbances were associated with greater fatigue, by patient-report (ρ=-0.41, P=0.007) and parent-report (ρ=-0.51, P<0.001). Greater functional ability was associated with less fatigue, by parent-report (ρ=0.30, P=0.02). Physical activity and ambulatory status were not associated with fatigue. Conclusions: Fatigue is a significant issue in DMD. Depressive symptoms and sleep disturbances are associated with fatigue, warranting attention in therapeutic strategies to reduce fatigue.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".